Motion In Turbulent Flow Research Articles

Modeling memory-enhanced stochastic suspended sediment transport with fractional Brownian motion in time-persistent turbulent flow

Modeling memory-enhanced stochastic suspended sediment transport with fractional Brownian motion in time-persistent turbulent flow

An artificial neural network model for recovering small-scale velocity in large-eddy simulation of isotropic turbulent flows

Small-scale motions in turbulent flows play a significant role in various small-scale processes, such as particle relative dispersion and collision, bubble or droplet deformation, and orientation dynamics of non-sphere particles. Recovering the small-scale flows that cannot be resolved in large eddy simulation (LES) is of great importance for such processes sensitive to the small-scale motions in turbulent flows. This study proposes a subgrid-scale model for recovering the small-scale turbulent velocity field based on the artificial neural network (ANN). The governing equations of small-scale turbulent velocity are linearized, and the pressure gradient and the nonlinear convection term are modeled with the aid of the ANN. Direct numerical simulation (DNS) and filtered direct numerical simulation (FDNS) provide the data required for training and validating the ANN. The large-scale velocity and velocity gradient tensor are selected as inputs for the ANN model. The linearized governing equations of small-scale turbulent velocity are numerically solved by coupling the large-scale flow field information. The results indicate that the model established by the ANN can accurately recover the small-scale velocity lost in FDNS due to filtering operation. With the ANN model, the flow fields at different Reynolds numbers agree well with the DNS results regarding velocity field statistics, flow field structures, turbulent energy spectra, and two-point, two-time Lagrangian correlation functions. This study demonstrates that the proposed ANN model can be applied to recovering the small-scale velocity field in the LES of isotropic turbulent flows at different Reynolds numbers.

Anchor chains—A simple low‐cost device to assist passage of small‐bodied mass fish

AbstractAttention has been placed on a variety of barriers that hinder fish passage in modern times. The most prevalent fish barriers were culverts which have negatively impacted waterway connectivity and fish habitats. For small‐bodied mass fish, high barrel velocities and turbulence have reduced fish swimming performance because of their weak swimming capabilities. In the present study, physical testing was conducted under controlled flow conditions to assess the extent and magnitude of turbulence characteristics, secondary flow and low‐velocity zones in a 0.5‐m‐wide box culvert barrel. Two cases were investigated; a reference case consisting of a smooth rectangular channel and a low‐cost design solution to improve upstream fish migration consisting of a single galvanized anchor chain fitted within a smooth rectangular channel. The single anchor chain was positioned towards one corner of the channel to induce asymmetric flow, reducing overall energy losses and enhancing the existing low‐velocity zone in the adjacent channel corner. The anchor chain induced a strong turbulent flow motion away from the anchor chain, characterized by higher Reynolds stress and turbulent kinetic energy, along with a distinct channel flow asymmetry. Conversely, the low‐velocity zone, between the anchor chain and the bottom channel corner, was significantly expanded with reduced longitudinal mean velocities and turbulent scales. Whilst the anchor chain link contributed to some complex localized wake flow, the anchor chain also influenced the distributions of normal turbulent stresses (v'z2 – v'y2), which in turn influenced the location of secondary flow cells. This secondary flow redirected low momentum fluid into the low‐velocity zones, setting the conditions for the favorable upstream passage of small‐bodied mass fish species.

Secondary motions in turbulent ribbed channel flows

Secondary motions in turbulent ribbed channel flows

Interplay of scales during the spatial evolution of energy-containing motions in wall-bounded turbulent flows

This article extends the previous investigation of the spatial evolution of energy-containing motions in wall-bounded turbulent flows (Kannadasan et al., J. Fluid Mech., vol. 955, 2023, R1) by examining their scale-interactions through spectral analysis based on the spanwise scale decomposition of turbulent kinetic energy and the Reynolds stress transport equation. The energy-containing motions located at the inflow of a turbulent channel flow are artificially removed and the interscale transport mechanisms involved in their spatial evolution are studied. This scale interaction analysis reveals the presence of a significant inverse transfer of streamwise Reynolds stress from the near-wall streaks to larger scales in the spatial evolution of energy-containing motions. This transfer is due to the spanwise variation of streamwise velocity fluctuations, represented by $\partial u'/\partial z$ , which is the primary mechanism of streak instability. The analysis presented in this study also shows that the inverse cascade of spanwise energy may correspond to the regeneration of streamwise vortices in the process of reactivating the self-sustaining mechanism in the spatial evolution of energy-containing motions.

Modified stochastic diffusion particle tracking model driven by skew Brownian motion: Analysis of sediment particle motion in turbulent flow under the effects of ejection and sweep.

Turbulent bursting events have been classified into outward interactions (Q1), ejections (Q2), inward interactions (Q3), and sweeps (Q4) in various studies. Ejections (Q2) and sweeps (Q4) have been identified as significant contributors to time consumption, momentum flux, and sediment flux. Additionally, research has shown that the distribution of these events varies nonuniformly at different bed elevations. Despite extensive investigations into the nonuniform distribution of turbulent bursting events, their impact on sediment transport has been rarely explored. In this work, we developed a modified stochastic diffusion particle tracking model (SD-PTM) driven by skew Brownian motion (SBM) using the stochastic Lagrangian approach to scrutinize sediment particle movement in turbulent flows. The model incorporates turbulent characteristics derived from a direct numerical simulation dataset, allowing for a comprehensive analysis of sediment particle dynamics. Moreover, the proposed model accounts for the nonuniform spatial distribution of ejection and sweep events, as well as the particle movement direction during these events. Numerical simulations of the model were conducted to trace sediment particle trajectories in the streamwise and vertical directions. The analysis of sediment transport involved calculating the variance of particle trajectories to examine anomalous diffusion. The model's performance was evaluated by comparing it with flow velocity and sediment concentration profiles obtained from measurements in previous studies. In conclusion, our study suggests that the motion of sediment particles in turbulent flow can be thoroughly investigated under extreme flow conditions using the modified SD-PTM driven by SBM.

Innovative and automated method for vortex identification

Context. Ubiquitous small-scale vortical motions are seen to occur in the solar atmosphere both in simulations and observations. They are thought to play a significant role in the local heating of the quiet chromosphere and corona. In a previous paper, we proposed a new method for the automated identification of vortices based on the accurate estimation of curvature centers; this method was implemented in the SWIRL algorithm. Aims. We aim to assess the applicability of the SWIRL algorithm to self-consistent numerical simulations of the solar atmosphere. The highly turbulent and dynamical solar flow poses a challenge to any vortex-detection method. We also conduct a statistical analysis of the properties and characteristics of photospheric and chromospheric small-scale swirling motions in numerical simulations. Methods. We applied the SWIRL algorithm to realistic, three-dimensional, radiative, magneto-hydrodynamical simulations of the solar atmosphere carried out with the CO5BOLD code. In order to achieve statistical validity, we analyzed 30 time instances of the simulation covering 2 h of physical time. Results. The SWIRL algorithm accurately identified most of the photospheric and chromospheric swirls, which are perceived as spiraling instantaneous streamlines of the horizontal component of the flow. Part of the identified swirls form three-dimensional coherent structures that are generally rooted in magnetically dominated intergranular lanes and extend vertically into the chromospheric layers. From a statistical analysis, we find that the average number densities of swirls in the photosphere and chromosphere are 1 Mm−2 and 4 Mm−2, respectively, while the average radius is 50 − 60 km throughout the simulated atmosphere. We also find an approximately linear correlation between the rotational speed of chromospheric swirls and the local Alfvén speed. We find evidence that more than 80% of the identified, coherent, vortical structures may be Alfvénic in nature. Conclusions. The SWIRL algorithm is a reliable tool for the identification of vortical motions in magnetized, turbulent, and complex astrophysical flows. It can serve to expand our understanding of the nature and properties of swirls in the solar atmosphere. A statistical analysis shows that swirling structures may be smaller, more numerous, and may rotate faster than previously thought, and also suggests a tight relation between swirls and the propagation of Alfvénic waves in the solar atmosphere.

Spatio-Temporal Visual Analysis of Turbulent Superstructures in Unsteady Flow.

The large-scale motions in 3D turbulent channel flows, known as Turbulent Superstructures (TSS), play an essential role in the dynamics of small-scale structures within the turbulent boundary layer. However, as of today, there is no common agreement on the spatial and temporal relationships between these multiscale structures. We propose a novel space-time visualization technique for analyzing the temporal evolution of these multiscale structures in their spatial context and, thus, to further shed light on the conceptually different explanations of their dynamics. Since the temporal dynamics of TSS are believed to influence the structures in the turbulent boundary layer, we propose a combination of a 2D space-time velocity plot with an orthogonal 2D plot of projected 3D flow structures, which can interactively span the time and the space axis. Besides flow structures indicating the fluid motion, we propose showing the variations in derived fields as an additional source of explanation. The relationships between the structures in different spatial and temporal scales can be more effectively resolved by using various filtering operations and image registration algorithms. To reduce the information loss due to the non-injective nature of projection, spatial information is encoded into transparency or color. Since the proposed visualization is heavily demanding computational resources and memory bandwidth to stream unsteady flow fields and instantly compute derived 3D flow structures, the implementation exploits data compression, parallel computation capabilities, and high memory bandwidth on recent GPUs via the CUDA compute library.

Revisiting “bursts” in wall-bounded turbulent flows

In this paper, we demonstrate that the problem of turbulent bursts can be tackled through a complex systems approach. Specifically, by considering both duration and intensity of the bursting events, one can incorporate the effect of bursts on the turbulence statistics at any specified scale of the flow, thereby allowing one to connect the origin of bursts to the presence of organized eddy motions in turbulent flows called coherent structures. Through our approach we discover a particular aspect of universality associated with turbulent bursts and contribute toward the development of next-generation turbulence models by creating a union between complex systems science and fluid mechanics.

Separating large-scale superposition and modulation in turbulent channels

The presence of very-large-scale motions in wall-bounded turbulent flows is commonly associated with their footprint in the form of the superposition of the large scales at the wall and the additional amplitude modulation of small-scale near-wall turbulence. These two phenomena are currently understood to be interlinked, with the superposed large-scale velocity gradient causing the modulation of small-scale activity in the proximity of the wall. To challenge this idea, we devise a numerical strategy that selectively suppresses either superposition or amplitude modulation, in an effort to isolate and study the remaining phenomenon. Results from our direct numerical simulations indicate that a positive correlation between the amplitude of the small scales in the near-wall region and the large-scale signal in the outer flow persists even when near-wall large-scale motions are suppressed – i.e. in absence of superposition. Clearly, this kind of correlation cannot be caused by the near-wall large-scale velocity or its gradients, as both are absent. Conversely, when modulation is blocked, the near-wall footprints of the large scales seem to disappear. This study has been carried out on channel flows at friction Reynolds number $Re_\tau =1000$ in both standard simulation domains and minimal streamwise units (MSUs), where the streamwise fluctuation energy is enhanced. The consistency of the results obtained by the two approaches suggests that MSUs can capture correctly this kind of scale interaction at a much reduced cost.

Model for calculating the hydraulic parameters of channels with a dynamically stable section

In today's climate change conditions, it is difficult to imagine agriculture as separate from irrigated agriculture. When taking water from the river, transferring a large number of river sediments along with water to crop fields through irrigation networks requires high carrying capacity and resistance to deformation from irrigation channels. In this process, correct assessment of the factors affecting the sedimentation of the flow and ensuring that the velocity in the channel is at the limit values determines the dynamic strength of the channels. In the paper, based on the analysis of some models representing suspended turbulent flow motion and a new generalized mathematical model based on the theory of interfering media, the equation for calculating the relative width of the channel (β) for two-phase turbulent flow containing suspended sediments and the interaction of the riverbed is taken into account. It was found that the results of this equation were very close to the results of field studies compared to existing computational methods compared with the values of field studies conducted on dynamically stable section channels and the values calculated by existing computational methods.

Deep learning method for the super-resolution reconstruction of small-scale motions in large-eddy simulation

A super-resolution reconstruction model for the subgrid scale (SGS) turbulent flow field in large-eddy simulation (LES) is proposed, and it is called the meta-learning deep convolutional neural network (MLDCNN). Direct numerical simulation (DNS) data of isotropic turbulence are used as the dataset of the model. The MLDCNN is an unsupervised learning model, which only includes high-resolution DNS data without manually inputting preprocessed low-resolution data. In this model, the training process adopts the meta-learning method. First, in the a priori test, the SGS turbulent flow motions in the filtered DNS (FDNS) flow field are reconstructed, and the energy spectrum and probability density function of the velocity gradient of the DNS flow field are reconstructed with high accuracy. Then, in the a posteriori test, the super-resolution reconstruction of the LES flow field is carried out. The difficulty of LES flow field reconstruction is that it contains filtering loss and subgrid model errors relative to the DNS flow field. The super-resolution reconstruction of the LES flow field achieves good results through this unsupervised learning model. The proposed model makes a good prediction of small-scale motions in the LES flow field. This work improves the prediction accuracy of LES, which is crucial for the phenomena dominated by small-scale motions, such as relative motions of particles suspended in turbulent flows.

Experimental and Computational Fluid Dynamics: decades of turbulent EFD/CFD complementarity

An overview of the parallel evolution of computations and experiments in fluid dynamics in the context of turbulent flows is given, viewed from an experimental side. It is evident that experiments can no longer be seen as only validations for computations and that forecasting for “numerical wind tunnels” is not yet valid. The growing evidence of organized motions in turbulent flows pushes in parallel both experiments and numerical approaches to develop new measurement technologies and numerical methods. Many tools and concepts are shared both by experiments and computations. These approaches appear to be quite complementary and both communities will gain from the mutual fertilization.

Experimental investigation on reactivity-controlled compression ignition (RCCI) combustion characteristic of n-heptane/ammonia based on an optical engine

Ammonia as a carbon-free fuel used in IC engines always suffers from large cyclic variations and high NOx emissions. Ammonia blending with high-reactivity fuels is recognized as an effective attempt to overcome these shortcomings. In this work, for the first time, the combustion and emission characteristics of n-heptane/ammonia were investigated under reactivity-controlled compression ignition (RCCI) conditions in an optical engine. An intake adapter was introduced to modify turbulent flow motion and n-heptane was directly injected to regulate mixture reactivity based on energy ratios. Particle image velocimetry (PIV) was employed for in-cylinder flow measurement, high-speed photography and instantaneous pressure acquisition were used for combustion evolutions, and Fourier transform infrared (FTIR) spectroscopy was adopted for NOx and NH3 emissions. The results show both mixture reactivity and turbulence have significant impacts on ammonia combustion. Specifically, n-heptane addition manifesting mixture reactivity dominates combustion processes at early-injection conditions, while the turbulence with increasing intensity becomes significant at late-injection conditions. Visualization images show that the initiation of initial flame kernels is controlled by the local distribution of n-heptane fraction, and that high n-heptane fraction at early injection or low n-heptane fraction at late injection conditions tends to induce homogeneous combustion. Flame stretch analysis confirms the promotion of mixture reactivity and turbulence motion on turbulent flame propagation and identifies that a high n-heptane fraction with swirl-tumble motion exhibits lower flame stretch sensitivity, especially for late-injection scenarios. Besides, low mixture reactivity with early injection and high mixture reactivity with late injection strategies can achieve high-efficiency combustion. However, when considering NOX/NH3 emissions, a high n-heptane fraction at late injection with swirl-tumble motion has the most potential to achieve the compromise between thermal efficiency and emissions. The present work demonstrates that with optimized fuel injection and flow arrangement, ammonia blending with high-reactivity fuels can achieve high-efficient combustion while maintaining NOx/NH3 emissions within reasonable levels.

Analysis of the in-cylinder flow of a DISI engine using high-speed particle image velocimetry

In addition to exploring electric drives, it is crucial to minimize emissions and improve the efficiency of transport based on internal combustion engines (ICE). For these, in particular, a significant reduction of emissions as well as a considerable efficiency of ICE are required. A reliable formation of an effective mixture prior to ignition and a fast, steady combustion process are two key elements that influence emissions and efficiency. While on the one hand, the air-fuel mixture is formed by strongly three-dimensional, time-dependent flow phenomena during the intake and compression stroke, the turbulence level of the flow near the approaching flame front has a direct impact on turbulent flame propagation. The flow field in the combustion chamber, on the other hand, is highly turbulent and sensitive to cycle-to-cycle variations (CCV). In order to understand the fundamental processes and interactions of the flow field, flow measurements with high spatial and temporal resolution are required. To analyze CCV, the resulting flow field data must be decomposed into its scales, since CCVs are different from random fluctuations due to turbulent flow motions. Besides velocity decomposition based on traditional Reynolds decomposition, which provides an average flow velocity and a fluctuation velocity, most studies include statistical and linear approaches such as proper orthogonal decomposition (POD) and Fast Fourier transformation (FFT). In this paper, time-resolved high-speed stereoscopic PIV (HS-SPIV) measurements on an optical single-cylinder engine are processed using a new nonlinear and transient decomposition method, namely the multivariate empirical mode decomposition (NA-MEMD) based on a data-driven decomposition algorithm. The decomposition is based on the inherent scales of the data and generates physically valid modal representations known as intrinsic mode functions (IMFs), which are arranged with respect to the contained scale values. The approach and the IMFs generated are described in detail using one engine cycle as an example. According to the results, three modes are obtained, the measurement noise and extremely tiny short-term scales, the turbulent scales, and the large-scale tumble vortex.

Interaction between near-wall streaks and large-scale motions in turbulent channel flows

The interactions between the near-wall streaks and the large-scale motions (LSMs) of the outer region of wall-bounded turbulent flows are investigated. The co-supporting hypothesis of Toh & Itano (J. Fluid Mech., vol. 524, 2005, pp. 249–262) is checked in full-scale channels at low to moderate Reynolds numbers, from two points of view. To study the top-down influence of the outer structures on the spanwise motion of the near-wall streaks, a method inspired by particle-image velocimetry is used to track the spanwise position of the streaks. Their spanwise advection velocity is found to be affected by the hierarchy of large-scale circulations in the logarithmic layer, but their spanwise streak density is only weakly related to the LSMs. The evidence suggests that a top-down influence exists and drives the drift of the streaks in the spanwise direction, as suggested by Toh & Itano (J. Fluid Mech., vol. 524, 2005, pp. 249–262), but that the hypothesised streak accumulation rarely occurs. Numerical experiments at $Re_{\tau }\thickapprox 535$ are then performed to clarify the role of the near-wall streaks in the generation and preservation of the outer LSMs. The results show that the merger of the near-wall streaks is only weakly correlated with the generation of the LSMs, and that removing the near-wall roots of the LSMs does not affect the evolution of their outer region. It is concluded that the bottom-up influence from the near-wall streaks is not essential for the LSM generation and preservation, also weakening the evidence for the co-supporting hypothesis.

Structure of turbulence in temporal planar jets

A detailed analysis of the structure of turbulence in a temporal planar turbulent jet is reported. Instantaneous snapshots of the flow and three-dimensional spatial correlation functions are considered. It is found that the flow is characterized by large-scale spanwise vortices whose motion is felt in the entire flow field. Superimposed to this large-scale motion, a hierarchy of turbulent structures is present. The most coherent ones take the form of quasi-streamwise vortices and high and low streamwise velocity streaks. The topology of these interacting structures is analyzed by quantitatively addressing their shape and size in the different flow regions. Such information is recognized to be relevant for a structural description of the otherwise disorganized motion in turbulent free-shear flows and can be used for the assessment of models based on coherent structure assumptions. Finally, the resulting scenario provides a phenomenological description of the elementary processes at the basis of turbulence in free-shear flows.

Open-channel flow over evolving subaqueous ripples

We have numerically investigated the turbulent flow and sediment grain motion in an open-channel flow configuration over a subaqueous sediment bed featuring two-dimensional transverse ripples at moderate Reynolds number and super-critical Shields number values. The simulation data, which were generated by means of particle-resolved direct numerical simulation, are the same as in our previous work (Kidanemariam & Uhlmann,J. Fluid Mech., vol. 818, 2017, pp. 716–743). By carefully choosing the computational box sizes, we were able to accommodate single ripple units which form over an initially flat sediment bed at a wavelength equal to the domain length. The ripples then evolve into their asymmetric shape relatively quickly and eventually migrate downstream steadily while maintaining their shape and size. In the present study, using a ripple-conditioned phase-averaging procedure, we are able to obtain novel insights into the evolution of the turbulent flow and particle motion over the bedforms, in particular the spatial structure of the basal shear stress and its relation to the particle flow rate. Our analysis confirms that the boundary shear-stress maximum is located upstream of the ripple crest, while the particle flow rate is essentially in phase with the ripple topology, with an average phase difference between the two in the range of 18–19 particle diameters for the considered parameter values. We were further able to confirm the link between the sediment flux relaxation behaviour and the observed shear-stress/geometry lag, by direct evaluation of the saturation length scale.

Properties of the compressibility and transport motion in wall-bounded turbulent flows at Mach 8

The compressibility effect and transport motion in highspeed turbulent boundary layer (TBL) is a fundamental problem because they dominate the average and statistical characteristics. Using the statistical methods and flow visualization technology, flat-plate TBLs at [Formula: see text] with high- and low-wall temperatures, [Formula: see text] and 1.9, are investigated based on the direct numerical simulation (DNS) datasets. Compared with previous studies, this study considers relative higher Mach number and strong cold wall temperature condition at the same time. First, the turbulent Mach number and turbulent intensity show that the compressibility effects are enhanced by the cooling process. Second, the high-order statistical moments and structure parameters confirm cold wall that causes stronger compressibility and the corresponding increased intensities of local streamwise and wall-normal transport motions. Finally, for uncovering the relationship between the compressibility effect and turbulent transport, more in-depth visualization analyses of velocity streaks are performed. It is found that ‘knot-like’ structures are generated when cooling the wall, and they lead to stronger intermittent, which results in the rapid increase of local compressibility effect and the wall-normal transport motion. Our research sheds light on providing a theoretical basis for further understanding the compressibility effects of TBL at high Mach number.

Theoretical Model Development for Energy Motion of Dusty Turbulent Flow of Fibre Suspensions in a Rotational Frame

Fibre suspension has garnered considerable attention in turbulent flows that are used in many industries. Solid particles, such as dust particles, notably affect the turbulent flow field in a rotational frame. In assessing their impacts, the dusty turbulent flow for fibre suspensions needs to be studied in a frame of rotation that can be substantially applied in many industries. This study, therefore, aims to build a theoretical model for the energy motion of dusty turbulent flow of fibre suspensions in a rotational frame. The turbulence momentum equation was considered to formulate the model in presence of dusty fluid rotating flow of fibre suspensions. The newly derived equation was derived in second‐order correlation tensors Fi,j, Wi,j, Gi,j, Si,j, Xi,j, Yi,j, Qi,j, and Ri,j at any two points in the flow domain, where the tensors were expressed as space, time, and distance functions. The developed model is a considerable improvement because it takes into account all of the potential influential parameters that could affect the motion of turbulent energy, such as dust particles, suspending particles (fibres), and rotating frame. However, the impact of these parameters on turbulence energy motion must be evaluated in order to assess the performance of turbulence systems utilized in a variety of industries, such as paper manufacturing. The present theoretical development will contribute to open up experimental and numerical research opportunities for the advancement of the industry, science, and technology.